Unfolding the innovation system for the development of countries: co-evolution of Science, Technology and Production

Abstract

We show that the space in which scientific, technological and economic developments interplay with each other can be mathematically shaped using pioneering multilayer network and complexity techniques. We build the tri-layered network of human activities (scientific production, patenting, and industrial production) and study the interactions among them, also taking into account the possible time delays. Within this construction we can identify which capabilities and prerequisites are needed to be competitive in a given activity, and even measure how much time is needed to transform, for instance, the technological know-how into economic wealth and scientific innovation, being able to make predictions with a very long time horizon. Quite unexpectedly, we find empirical evidence that the naive knowledge flow from science, to patents, to products is not supported by data, being instead technology the best predictor for industrial and scientific production for the next decades.

References in corpus (16)

• The Building Blocks of Economic Complexity
• The structure and dynamics of multilayer networks
• The Product Space Conditions the Development of Nations
• How to project a bipartite network?
• Recommender Systems
• Universality of citation distributions: towards an objective measure of scientific impact
• The statistical mechanics of networks
• The Statistical Physics of Real-World Networks
• Randomizing bipartite networks: the case of the World Trade Web
• Temporal effects in the growth of networks
• The Scientific Competitiveness of Nations
• Inferring monopartite projections of bipartite networks: an entropy-based approach
• Computational Socioeconomics
• How the Taxonomy of Products Drives the Economic Development of Countries
• Statistically validated network of portfolio overlaps and systemic risk
• Empirical confirmation of creative destruction from world trade data

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• The Policy Implications of Economic Complexity
• Meta-validation of bipartite network projections
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• Measuring Scientific Brain Drain with Hubs and Authorities: a Dual Perspective
• Universal Database for Economic Complexity
• Equivalence between the Fitness-Complexity and the Sinkhorn-Knopp algorithms
• Inferring comparative advantage via entropy maximization
• The Evolution of Competitiveness across Economic, Innovation and Knowledge production activities
• Export complexity, industrial complexity and regional economic growth in Brazil
• Italian Twitter semantic network during the Covid-19 epidemic